The Essentialness of “Essential Math for Data Science”
Andre Oporto
Gain a deeper understanding of the mathematics behind AI and how generative tools like ChatGPT work.
Gradient descent IRL: “Dolgie Mountains, South Ural” Photo by Daniil Silantev on Unsplash
There’s always more to learn about Artificial Intelligence, with opportunities to study several areas, including Python libraries, Deep Learning tools such as TensorFlow, and, most recently, Generative AI. You may still wish for a fuller understanding of how all these tools work at a fundamental level.
The math and science behind these technologies can be daunting.
Enter Essential Math for Data Science by Thomas Nield. This book will guide you in learning and becoming comfortable with the fundamentals: statistics and probabilities, derivatives, regressions, and how neural nets and Deep Learning work. All the things that make the magic of Generative AI tools like ChatGPT happen.
You’ll gain insights into the benefits and pitfalls of different solutions, including why biased data and overfitting can lead to incorrect (and possibly disastrous) results, and how to prevent these situations. Those chatbot hallucinations happen for a reason. You will be able to think about, and in many cases implement, validations for the answers your solution generates. When someone presents you with statistics such as accuracy with unequivocal certainty, you’ll know to ask the right questions to dig deeper. “Trust but verify.”
I cannot recommend this book enough. I’ve had the opportunity to learn Python, scikit-learn, and TensorFlow, and apply them in various experiments, POCs and applications. Yet I always felt like I should explore more regarding the math and statistics that underpin it all. Early on, I took Andrew Ng’s original Machine Learning online course that emphasized math concepts more, which was extremely helpful, but in hindsight, only the first step. I could do more and still stay on course in my AI journey.
This book has given me what I feel is a significant leap. I’m confident that my skills can now be applied more effectively in other areas, especially Generative AI and financial applications, which are my current focus.
I’m excited to see what comes next.
See my completed exercises for this book on GitHub, including some of my custom code libraries and examples.